检索结果-内蒙古大学图书馆

19th Annual Conference of China Electrotechnical Society, ACCES 2024

作者： Zuo, Peng Li, Weili Liu, Xiaoke Liu, Wenmao Li, Dan Qiao, Tianhuai School of Electrical Engineering Beijing Jiaotong University Beijing China Department of Electrical Engineering Tsinghua University Beijing China College of Computer and Control Engineering Northeast Forestry University Harbin China

ISBN: (纸本)9789819613861

With the trend towards larger-scale wind generators, the internal physical field and control strategy of high-capacity generator is becoming increasingly complex. The physical field change law inside the generator is often overlooked by the conventional wind energy conversion system (WECS) model. Therefore, developing a comprehensive and precise WECS model is essential for the safe operating of wind generators. Aiming at the above problems, this paper takes a 5 MW direct-drive permanent magnet synchronous generator (PMSG) as an example, and establishes a multi-domain coupling model. This approach can be used to investigate how the external characteristics of PMSG change under different operating conditions. Additionally, it has the ability to monitor how eddy currents are distributed in permanent magnets (PM), supporting generator design theoretically. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Permanent magnets

来源：评论

学校读者我要写书评

暂无评论

UAV Enabled Sustainable IoT Network with OTPDRL 26

UAV Enabled Sustainable IoT Network with OTPDRL

引用

26th International Conference on computer Supported Cooperative Work in Design, CSCWD 2023

作者： Wang, Tiantian Liu, Lei Sun, Hongbo Hu, Jia Shandong University School of Software Jinan China YanTai University School of Computer and Control Engineering YanTai China Exeter University Computer Science United Kingdom

ISBN: (纸本)9798350331684

Integrating large-scale sensors into the network has become a research hotspot for its promising flexibility in monitoring vitally critical wild areas. However, the existing Internet of Things (IoT) systems are limited due to the lack of a stable power supply, which seriously affects the system's sustainability. The combination of sensors equipped with cordless power batteries and long-distance power transmission has ushered in a new era. Using the unmanned aerial vehicles (UAVs) to charge the battery ensures the flexibility and sustainability of the sensor in environmental detection. In this work, we aim to provide a solution for maintaining the sustainability of the sensors while optimizing UAV trajectory to minimize the overall energy consumption of UAV. Since deep reinforcement learning successfully solves the NP-hard combinatorial optimization problem, deep reinforcement learning is introduced in this work to obtain a feasible solution. We formulate the trajectory planning of UAV as a Markov decision problem and employ a deep reinforcement learning (DRL) model based on an attention mechanism to find the optimal policy efficiently, named the optimal trajectory planning algorithm based on DRL (OTPDRL). The experimental results suggest the OTPDRL obtains a good trade-off between performance gain and computational time. © 2023 IEEE.

关键词： Unmanned aerial vehicles (UAV)

来源：评论

学校读者我要写书评

暂无评论

Chinese Nested Entity Recognition Benchmark in the Field of Naval Warfare

Chinese Nested Entity Recognition Benchmark in the Field of ...

引用

2024 IEEE International Conference on Unmanned Systems, ICUS 2024

作者： Zhang, Shengjie Li, Qi Kou, Yueping Wang, Jun Li, Zhengwei Wu, Baolei School of Computer Science and Technology China University of Mining and Technology Xuzhou China School of Information and Control Engineering China University of Mining and Technology Xuzhou China

ISBN: (纸本)9798350384185

Named entity recognition (NER) is a fundamental task in natural language processing and a key technology for building knowledge graphs. However, the performance of NER is often limited by domain-specific characteristics. For unpopular Chinese entity recognition fields, such as naval warfare, NER typically performs poorly due to the lack of sufficient pre-trained models and labeled data. Furthermore, the naval warfare field includes numerous specialized terms and complex domain knowledge, with nested structures and physical relationships that are uncommon in conventional corpora, posing additional challenges for NER. To address these issues, we manually construct a high-quality naval warfare domain corpus. We also propose a new nested entity recognition framework, which fully leverages entity boundary information, enhances the learning of entity adjacency modeling information, and uses multi-scale convolution to obtain richer span feature representation. Experiments demonstrate the effectiveness of this method in four Chinese NER corpora. © 2024 IEEE.

关键词： Naval warfare

来源：评论

学校读者我要写书评

暂无评论

Detecting the One-Shot Dummy Attack on the Power Industrial control Processes With an Unsupervised Data-Driven Approach

引用

IEEE/CAA Journal of Automatica Sinica 2023年第2期10卷 550-553页

作者： Zhenyong Zhang Yan Qin Jingpei Wang Hui Li Ruilong Deng the State Key Laboratory of Public Big Data and the College of Computer Science and Technology Guizhou UniversityGuiyang 550025China the School of Chemical and Biomedical Engineering Nanyang Technological UniversitySingapore 639798Singapore the State Key Laboratory of Industrial Control Technology and the College of Control Science and Engineering Zhejiang UniversityHangzhou 310027China IEEE

Dear Editor,Dummy attack(DA), a deep stealthy but impactful data integrity attack on power industrial control processes, is recently recognized as hiding the corrupted measurements in normal measurements. In this letter, targeting a more practical case, we aim to detect the oneshot DA, with the purpose of revealing the DA once it is ***, we first formulate an optimization problem to generate one-shot DAs. Then, an unsupervised data-driven approach based on a modified local outlier factor(MLOF) is proposed to detect them.

关键词： Dummy Power letter

来源：评论

学校读者我要写书评

暂无评论

Minimum Epsilon-Kernel Computation for Large-Scale Data Processing

引用

Journal of computer Science & Technology 2022年第6期37卷 1398-1411页

作者： Hong-Jie Guo Jian-Zhong Li Hong Gao School of Computer Science and Technology Harbin Institute of TechnologyHarbin 150001China Faculty of Computer Science and Control Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518000China

Kernel is a kind of data summary which is elaborately extracted from a large *** a problem,the solution obtained from the kernel is an approximate version of the solution obtained from the whole dataset with a provable approximate *** is widely used in geometric optimization,clustering,and approximate query processing,etc.,for scaling them up to massive *** this paper,we focus on the minimumε-kernel(MK)computation that asks for a kernel of the smallest size for large-scale data *** the open problem presented by Wang et *** whether the minimumε-coreset(MC)problem and the MK problem can be reduced to each other,we first formalize the MK problem and analyze its *** to the NP-hardness of the MK problem in three or higher dimensions,an approximate algorithm,namely Set Cover-Based Minimumε-Kernel algorithm(SCMK),is developed to solve *** prove that the MC problem and the MK problem can be Turing-reduced to each ***,we discuss the update of MK under insertion and deletion operations,***,a randomized algorithm,called the Randomized Algorithm of Set Cover-Based Minimumε-Kernel algorithm(RA-SCMK),is utilized to further reduce the complexity of *** efficiency and effectiveness of SCMK and RA-SCMK are verified by experimental results on real-world and synthetic *** show that the kernel sizes of SCMK are 2x and 17.6x smaller than those of an ANN-based method on real-world and synthetic datasets,*** speedup ratio of SCMK over the ANN-based method is 5.67 on synthetic ***-SCMK runs up to three times faster than SCMK on synthetic datasets.

关键词： approximate query processing kernel large-scale dataset NP-hard

来源：评论

学校读者我要写书评

暂无评论

Analysis of Subsynchronous Oscillations Caused by Interactions of DFIG-Based Farms and SVGs

引用

IEEE Transactions on Power Systems 2025年第2期40卷 1570-1582页

作者： Li, Kejiang Chen, Wuhui Qin, Wei Li, Canbing Qin, Wenping Qiu, Jing Guo, Xiaolong Chang, Xiqiang Liu, Defu College of Electrical and Power Engineering Taiyuan030024 China Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering Shanghai200240 China The University of Sydney School of Electrical and Computer Engineering SydneyNSW2006 Australia State Grid Xinjiang Electrical Power Company Ltd. Xinjiang Control Center for Power Dispatching Wulumuqi830002 China

The static var generators (SVGs) installed at the point of common coupling (PCC) of wind farms can significantly impact the sub-synchronous oscillation (SSO) performance of the power system with grid-connected wind farms. For example, in 2017 multiple SSO events were caused by interactions among a doubly fed induction generator (DFIG) based farm, constant reactive power mode (CRPM) based SVGs, and the weak grid in Xinjiang, China. This paper reveals the mechanisms of the SSO caused by the interaction among DFIG-based farms, SVGs with different control modes, and weak grids. It is discovered that CRPM-based SVGs with low current controller bandwidths (CCBWs) can suppress SSOs in the power system with grid-connected DFIG-based farms, but that constant voltage mode (CVM) based SVGs and constant power factor mode (CPFM) based SVGs can worsen the SSO performance of the system. Furthermore, it is revealed why the amplitude of the super-synchronous component is larger than the sub-synchronous component in these events by deriving their amplitude ratio equation. Finally, the theoretical analysis results are verified by the small-signal method and electromagnetic transient (EMT) simulation. © 1969-2012 IEEE.

关键词： Phase locked loops

来源：评论

学校读者我要写书评

暂无评论

U-net Model with Particle Swarm Optimization for Floating Raft Information Extraction 13

U-net Model with Particle Swarm Optimization for Floating Ra...

引用

13th International Conference on Information Science and Technology, ICIST 2023

作者： Liu, Yuanyue Fan, Jianchao Zhao, Jin Wang, Jun School of Computer Science and Engineering Chongqing Three Gorges University Chongqing China School of Control Science and Engineering Dalian University of Technology Dalian China

ISBN: (纸本)9798350313925

Extracting the sea area of Marine floating raft culture is contributed to the rational use of aquaculture resources. The availability of remote sensing technology can dynamically detect aquaculture rafts. As a classical semantic segmentation model, U-net can also be beneficial to extract the synthetic aperture radar images of marine cultivation. However, the parameters of U-net are customarily set by experts based on experience and cannot be changed dynamically. In this paper, a method for flexibly designing U-net model parameters by particle swarm optimization is presented. Treat individuals with diverse parameters as a swarm and randomly initialize the encoded information, allowing each individual to apply appraisal indicators for fitness evaluation. Implementing particle updates and iteratively improving model parameters in interactive learning between individuals and populations. The experimental results demonstrate that the model can obtain competitive outcomes on multiple evaluation indicators after parameter optimization. © 2023 IEEE.

关键词： Iterative methods

来源：评论

学校读者我要写书评

暂无评论

Communication Countermeasure Strategy Decision-Making Based on Incomplete Information Game 27

Communication Countermeasure Strategy Decision-Making Based ...

引用

27th International Conference on Advanced Communications Technology, ICACT 2025

作者： Liu, Jinyue Gao, Xiang Yang, Haowei Zhang, Jihao Liu, Yuhan Gong, Peng National Key Laboratory of Mechatronic Engineering and Control School of Mechatronical Engineering Beijing Institute of Technology Beijing China Institute of Computer Application Technology Norinco Group Beijing China

ISBN: (纸本)9791188428137

In modern battlefields, the stability of wireless communications is crucial for intelligence transmission, command coordination, and maintaining strategic advantage. However, with the rapid advancement of communication technologies, the electromagnetic environment has become increasingly complex, making intelligent decision-making in communication countermeasures a prominent research focus. However, most existing studies adopt deep learning and reinforcement learning methods, which require extensive data samples and computational resources. To address these limitations, this paper proposes a game-theoretic model for intelligent radio communication countermeasures under incomplete information. It quantitatively evaluates common attack and defense tactcis used in communication countermeasures and explores the mixed-strategy equilibrium of the game when both the attackers and defenders consist of multiple types. Furthermore, simulation-based comparative analyses are conducted to assess the factors influencing the utility of both the attacker and defender. The findings offer theoretical insights and decision-making support for the deployment of communication countermeasure strategies in practical military operations, contributing to significant strategic value. © 2025 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.

关键词： Deep reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

State of health estimation of lithium-ion batteries based on TiDE

State of health estimation of lithium-ion batteries based on...

引用

2024 China Automation Congress, CAC 2024

作者： Li, Hui Cui, Fangshu Shi, Yuanhao Wang, Bohui School of Electrical and Control Engineering North University of China Taiyuan China School of Computer Science and Technology North University of China Taiyuan China School of Cyber Science and Engineering Xi'an Jiaotong University Xi'an China

ISBN: (纸本)9798350368604

Given the widespread use of lithium-ion batteries, accurately forecasting their State of Health (SOH) is crucial for ensuring the secure and reliable operation of equipment. The local capacity regeneration during battery degradation can undermine prediction accuracy. This research introduces an MDT-FOA+TiDE approach for predicting SOH in lithium-ion batteries using multidimensional time series data. Initially, capacity and various feature data from the degradation process were collected and health indicators were derived. Features with high correlation to capacity were integrated into multidimensional time series. Subsequently, the Time-series Dense Encoder (TiDE) model was employed for training and prediction, while the Fox Optimization Algorithm (FOA) was used for model optimization. Experimental results using the NASA dataset demonstrate that the proposed approach outperforms SVR and LSTM models that utilize univariate data and MDT-TiDE model without FOA optimization. © 2024 IEEE.

关键词： lithium-ion batteries local capacity regeneration multidimensional time series state of health

来源：评论

学校读者我要写书评

暂无评论

A Registration and Fusion Method of 3D Cross-source Point Cloud Data for Modeling Accurate Models of Small Celestial Bodies

A Registration and Fusion Method of 3D Cross-source Point Cl...

引用

2024 IEEE International Conference on Robotics and Biomimetics, ROBIO 2024

作者： He, Xuan Zhao, Qingjie Lv, Xingchen Wang, Lei Liu, Wangwang School of Computer Science and Technology Beijing Institute of Technology Beijing100081 China Beijing Institute of Control Engineering Beijing100190 China

ISBN: (纸本)9781665481090

High-precision three-dimensional models of small celestial bodies are important for deep space exploration tasks. The homologous point cloud obtained from a single sensor has limitations in terms of accuracy and density. For example, the point cloud obtained by RGB camera has rich information and high density, but low precision. The point cloud obtained by laser scanning has high precision but low density. Therefore, we hope to register and fuse the point clouds obtained from different sensors, synthesize the advantages of cross-source point clouds obtained from different source domains, and improve the density, accuracy and other aspects of small celestial point clouds. To solve the common problems of cross-source point clouds, we adopt an end-to-end feature measurement point cloud registration framework, which does not need to search the corresponding points between two point clouds, and reduces the difficulty of processing cross-source point cloud data. Aiming at the problem that some stray points on the registered point cloud surface affect the accuracy of the point cloud, a point cloud fusion optimization method based on Euclidean distance is proposed. The stray points around the point cloud are removed to reduce the loss of normal points. The accuracy of point cloud is improved by the fusion after registration. Experiments show that the proposed method can effectively improve the density and accuracy of small celestial body models. © 2024 IEEE.

关键词： Laser applications

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：